The Woman BossThe Woman BossThe power and prominence of AI today means that we are already in the future. From helping doctors detect diseases to supporting research, improving productivity, and making everyday tasks easier, AI is transforming how we live and work.
A study by MIT found that using AI reduced the time needed to complete certain writing tasks by 40%. Beyond individual productivity, the International Monetary Fund estimates that AI could also increase global economic growth by around half a percentage point annually if managed well. But what happens when a technology that promises to level the playing field is introduced into a world that is already unequal?
I want to put it to you that there’s a contradiction between the promise of greater productivity and development and the unequal conditions under which countries, particularly African countries, are adopting it. In fact, I want to argue that, left as it is, the prominence of AI worldwide would only serve to deepen developmental inequalities. I will build this argument around four different points.
Before I do so, I would like to highlight some of the existing inequalities between Africa and the rest of the world. According to the International Telecommunication Union, only 36% of Africa’s population used the internet in 2025, compared to 92% in Europe. Furthermore, the 2024 Government AI Readiness Index gave sub-Saharan Africa an average score of just 32.7 out of 100. These figures show that countries are not starting from the same position. Some already have the financial resources, infrastructure, and technological capacity needed to take full advantage of AI, while others are still struggling with the basic conditions required to do so.
That brings me to my first point, which is the affordability gap. Even in Africa, there is growing adoption and usage of AI tools. Many of these tools offer free versions, making them accessible to more people. However, access to the most advanced versions and features often comes at a cost. There are usually subscription fees and, in some cases, additional computing costs, which create further barriers. Now, considering the existing economic and financial inequalities between Africa and other parts of the world, this restricts individuals, organizations, and, consequently, the African continent from meaningfully adopting and benefiting from these tools.
This becomes a paradox because it has an unintended consequence, which is that those who could benefit more significantly from AI tools in terms of productivity and development are often the least able to afford them. Meanwhile, individuals and institutions with more financial resources are able to fully utilize them, thereby widening their productivity advantage and exacerbating the development gap.
After you look at financial resources, you look at physical resources. By this, I mean infrastructure. AI does not operate in isolation. The quality of AI tools and outputs depends on a lot of contributing factors. It depends on the availability of reliable electricity, internet connectivity, computing infrastructure, and good technical support.
According to the International Energy Agency, around 600 million people in sub-Saharan Africa did not have access to electricity in 2024. These are the foundations for AI, and where these foundations are below standard, inaccessible, or expensive, they become additional barriers to adoption and effective usage for individuals, startups, public institutions, and local organizations.
What this means is that the identified gap is a partial reflection of a much older and much deeper development divide. The countries and regions that have stronger digital infrastructure will naturally be able to integrate new technologies more quickly, while others, like those in Africa, do not have that luxury. They have the option of overcoming the barriers that make using these technologies difficult first and lagging behind in the AI race, or trying to adopt and integrate AI into their systems and processes while navigating an unconducive infrastructural environment.
My next argument on why the adoption of AI globally could potentially deepen the development and productivity divide, especially between Africa and the rest of the world, is the problem of brain drain. Despite its many challenges, Africa is not short of talent and human resources. There are so many talented Africans capable of actually contributing to AI development and innovation on the continent. However, the technology ecosystems that we have locally struggle to compete with international companies that offer higher salaries, better research environments, more advanced infrastructure, and just a more conducive environment all around.
When skilled professionals leave for these opportunities, what happens is that the benefits of their expertise accumulate disproportionately in the institutions and economies that can afford to recruit them, as opposed to the economies that they actually come from. This is not to say that Africans and African professionals should not aspire to pursue global opportunities, but that local ecosystems need to have the conditions to attract, retain, and benefit from their expertise.
Last but not least, arguably the most pervasive hurdle for AI and technology in general in Africa is governance. Across all relevant spheres in the technology ecosystem, you will find governance gaps. Domestically, these include weak regulatory laws and policies, limited enforcement and monitoring capacity, and inadequate data protection, just to name a few. These gaps leave African countries exposed and vulnerable to the misuse of data, algorithmic biases, and the unchecked influence of powerful technology companies.
Sadly, the governance challenge does not end at the national level. It also extends to the international level, where decisions about the development and use of AI have consequences for African countries, even when they have limited influence over those decisions. According to UN Trade and Development (UNCTAD), 118 countries, mostly developing countries, were not represented in any of seven major international AI governance initiatives examined in its 2025 report. Meanwhile, only the G7 countries participated in all seven. This shows how global AI governance remains largely shaped by wealthier countries, while developing regions like Africa have limited influence over decisions that also affect them. This is a point of concern because limited influence risks having African realities and development priorities overlooked, while countries with greater resources and influence are better positioned to shape these decisions around their own needs. This brings forth the conversation of data and technology sovereignty, but I digress, and for the purpose of this essay, I will not be exploring these concepts beyond the point of mentioning.
Addressing these challenges requires effective regulations, accountable institutions, meaningful public participation, and stronger and more equitable African representation in global AI governance because without these, Africa risks being disadvantaged not only in its ability to use AI, but also in its ability to shape the rules under which AI is developed and used.
In conclusion, AI in and of itself is neither an equalizer nor a driver of inequality. Its impact on Africa’s development, as with any economic tool or resource, depends on who accesses, controls, and benefits from its use. As such, African institutions, especially governments, need to move beyond just adoption to building the continent’s capacity to shape, regulate, and benefit from AI and other emerging technologies.
Ultimately, while AI could potentially deepen inequalities as it stands, it could also become an important tool in closing the development inequality gaps between Africa and the rest of the world.
